Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 477 50 755 149 509 75 416 421 444 993 644 419 70 754 843 683 826 55 409 344
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] 826 NA 477 754 NA 344 421 70 419 509 50 993 644 55 444 149 75 843 409 755 416 683 NA
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 5 4 3 2 4 4 1 5 4 1
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y" "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y" "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "v" "e" "h" "r" "q" "F" "L" "N" "G" "H"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
[1] 10
which( manyNumbersWithNA > 900 )
[1] 12
which( is.na( manyNumbersWithNA ) )
[1] 2 5 23
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
[1] 993
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
[1] 993
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
[1] 993
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "F" "L" "N" "G" "H"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "v" "e" "h" "r" "q"
manyNumbers %in% 300:600
[1] TRUE FALSE FALSE FALSE TRUE FALSE TRUE TRUE TRUE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE
which( manyNumbers %in% 300:600 )
[1] 1 5 7 8 9 12 19 20
sum( manyNumbers %in% 300:600 )
[1] 8
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] "large" NA "small" "large" NA "small" "small" "small" "small" "large" "small" "large" "large" "small" "small" "small" "small" "large"
[19] "small" "large" "small" "large" NA
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "large" "UNKNOWN" "small" "large" "UNKNOWN" "small" "small" "small" "small" "large" "small" "large" "large" "small"
[15] "small" "small" "small" "large" "small" "large" "small" "large" "UNKNOWN"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] 826 NA 0 754 NA 0 0 0 0 509 0 993 644 0 0 0 0 843 0 755 0 683 NA
unique( duplicatedNumbers )
[1] 5 4 3 2 1
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 5 4 3 2 1
duplicated( duplicatedNumbers )
[1] FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE
which.max( manyNumbersWithNA )
[1] 12
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 993
which.min( manyNumbersWithNA )
[1] 11
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 50
range( manyNumbersWithNA, na.rm = TRUE )
[1] 50 993
manyNumbersWithNA
[1] 826 NA 477 754 NA 344 421 70 419 509 50 993 644 55 444 149 75 843 409 755 416 683 NA
sort( manyNumbersWithNA )
[1] 50 55 70 75 149 344 409 416 419 421 444 477 509 644 683 754 755 826 843 993
sort( manyNumbersWithNA, na.last = TRUE )
[1] 50 55 70 75 149 344 409 416 419 421 444 477 509 644 683 754 755 826 843 993 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 993 843 826 755 754 683 644 509 477 444 421 419 416 409 344 149 75 70 55 50 NA NA NA
manyNumbersWithNA[1:5]
[1] 826 NA 477 754 NA
order( manyNumbersWithNA[1:5] )
[1] 3 4 1 2 5
rank( manyNumbersWithNA[1:5] )
[1] 3 4 1 2 5
sort( mixedLetters )
[1] "e" "F" "G" "h" "H" "L" "N" "q" "r" "v"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 10.0 6.5 6.5 8.5 2.5 8.5 2.5 4.5 1.0 4.5
rank( manyDuplicates, ties.method = "min" )
[1] 10 6 6 8 2 8 2 4 1 4
rank( manyDuplicates, ties.method = "random" )
[1] 10 7 6 8 3 9 2 4 1 5
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.0000000 -0.5000000 0.0000000 0.5000000 1.0000000 0.2263173 0.9131569 1.0953023 1.5933083 1.2130246 -0.1663922 -2.0174914 -0.8576936
[14] 1.2654270 1.5191323
round( v, 0 )
[1] -1 0 0 0 1 0 1 1 2 1 0 -2 -1 1 2
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 0.2 0.9 1.1 1.6 1.2 -0.2 -2.0 -0.9 1.3 1.5
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 0.23 0.91 1.10 1.59 1.21 -0.17 -2.02 -0.86 1.27 1.52
floor( v )
[1] -1 -1 0 0 1 0 0 1 1 1 -1 -3 -1 1 1
ceiling( v )
[1] -1 0 0 1 1 1 1 2 2 2 0 -2 0 2 2
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 x 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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